Efficient responses to climate change require accurate estimates of both aggregate damages and where and to whom they occur. While specific case studies and simulations have suggested that climate change disproportionately affects the poor, large-scale direct evidence of the magnitude and origins of this disparity is lacking. Similarly, evidence on aggregate damages, which is a […]

Using a dataset of 15 million UK job adverts from a recruitment website, we construct new economic statistics measuring labour market demand. These data are ‘naturally occurring’, having originally been posted online by firms. They offer information on two dimensions of vacancies—region and occupation—that firm-based surveys do not usually, and cannot easily, collect. These data […]

Barber and Odean study the relationship between trading activity and returns. They find that households who trade more have a lower net return than other households. They argue that these results cannot emerge from a model with rational traders and instead attribute these findings to overconfidence. In contrast, we find that household financial choices generated […]

Chinese local governments wield their enormous political power and administrative capacity to provide “special deals” for favored private firms. We argue that China’s extraordinary economic growth comes from these special deals. Local political leaders do so because they derive personal benefits, either political or monetary, from providing special deals. Competition between local governments limits the […]

We introduce a computationally tractable dynamic equilibrium model of the automobile market where new and used cars of multiple types (e.g. makes/models) are traded by heterogeneous consumers. Prices and quantities are determined endogenously to equate supply and demand for all car types and vintages, along with the ages at which cars are scrapped. The model […]

Falling Oil Price and Unemployment: Inferences from TMOS.

With oil prices at year’s lowest, U$55.25 per barrel, everyone wonders about possible spillovers in the United States national economy. Although many people started to enjoy low prices of gas and others turned recklessly their furnace up during the winter, many other people started worrying about their own jobs, inflation/deflation, future demand for new orders and future working hours, among other concerns. Manufactured goods producers in Texas are among the ones who worry the most when oil prices go down. Usually they are the first economic sector to perceive drastic changes in the economy. They almost can smell future crisis.

Graph # 1.

Every month roughly 107 Texans manufacturing-firm-executives take time out of their busy schedules to answer a couple of question that the Federal Reserve Bank of Dallas send them in the Texas Manufacturing Outlook Survey (TMOS). Those questions can be grouped in two subsets: first a group of question inquiring about economic activity changes from previous month (Summarized findings in Graph # 3); and a second group of question inquiring about expected economic activity six month from the date they fill out the survey (Summarized findings in Graph # 2).

December 2014 TMOS’ findings (Briefly):

Although mostly all indicators marked positive from November 2014 to December 2014 (Graph # 3), it is possible to perceive a moderate optimism among manufacturers who responded the Texas Manufacturing Outlook Survey (TMOS). Economic activity expectations were actually adjusted as the price of oil went down (Graph #2). Responders of the TMOS in December 2014 filled out the forms between December 15th and December 23rd. It is precisely the same week in which oil prices went down below U$60 a barrel. This very fact may have had an impact for expected economic activity on them. TMOS data showed that “Production” expectations six months from December 2014 were adjusted 6.7 points less than the previous month of November. This change could mean two thing, either Texans manufacturers were over-optimistic in November 2014, or they started to seriously feel the economic spillover of dropping oil prices during December of the same year.

So far not so bad for manufacturers. But how about workers? Texans manufacturers that responded the survey do not expect future increase in hours worked for their employees, at least for the six months following December 2014. The index “Hours worked” dropped almost toward negative terrain (0.4). Notice that -just one month before- the same index was at 14.2 (Graph #2). This is bad news for workers if you consider that expected sales drive current business hiring. In other words, a manager expecting an increase of sales tomorrow will decide to hire people today in order to fulfill future demand. Otherwise, a manager who does not expect sales to be higher tomorrow will not hire today.

Graph # 2.

Another two indicators severely adjusted from November to December were “Shipments” and “Prices Received for Finished Goods”. The former indicator dropped 8.5 points whereas the latter did so by 11.5 points in the index. Both indicators remained positive and solid, but it is also true that both went down.

Graph # 3.

Obviously, the US economy works as a system in which someone losses’ is somebody else’s gains. In other words, although low oil prices may hit the economy the way described above, it also may create and foster job opportunities for many other people in other economic sectors. Nonetheless, it is important for policy makers and business leaders to track these trends in order to better adjust where and whenever it is necessary.

About TMOS and Texas:

Economists at the Federal Reserve Bank of Dallas construct a series of indexes by taking the answers responders give in the Texas Manufacturing Outlook Survey (TMOS). “Survey responses are used to calculate an index for each indicator. Each index is calculated by subtracting the percentage of respondents reporting” either a decrease or an increase. TMOS is a monthly survey of area manufacturers. It is important to note that besides oil industry in Texas, this state produces roughly 9.5% of the country’s manufacturing output, as well as roughly 10% of nation’s computer and electronics products. Texas ranks first in manufactured goods exports.